Abstract: Systems, methods, and devices are described for monitoring and protecting electronic hardware, data assets, and the facility itself, particularly well-suited to monitoring remote facilities and resources in edge locations, including for determining door state for both equipment and personnel doors, and for determining values of one or more environmental parameters, using optical image analytics. An example system includes one or more edge-located hardware monitoring devices having one or more physical sensors, and custom software distributed across edge, cloud, mobile, and enterprise platforms. An example monitoring device can include an embedded computer, various sensors of different types, one or more cameras, a power supply, and several communication interfaces. All or virtually all sensing and processing capabilities can be integrated into the edge device, which utilizes low-cost sensors and video analytics to monitor the environment.

Abstract: Disclosed herein are systems and methods for classifying traffic indicators to detect intersection crossings by a vehicle. A computing device can receive a sequence of frames captured by a capture device mounted to the vehicle, and generate an intersection status data structure for each frame in the sequence of frames using a full-frame classification model. The computing device can also classify a set of features detected in each frame using an object detection model, and detect an intersection crossing event based on the intersection status data structure of each frame and the classification of each of the set of features detected in each frame. The systems and methods described herein improve upon existing traffic light classification models by using a full-frame intersection classification model in connection with traditional object tracking techniques, thereby reducing false-positive crossing-event detection and improving the accuracy of classification in a variety of environmental conditions.

Abstract: Subject matter disclosed herein relates to systems, devices, and/or processes for processing signals relating to surfaces that may be viewable by subjects though one or more devices. In an embodiment, a surface may include one or more devices embedded therein to provide one or more signals to define a portion of the surface.

Abstract: Methods, devices and computer-readable media for processing a compressed video to perform an inference task are disclosed. Processing the compressed video may include selecting a subset of frame encodings of the compressed video, or zero or more modalities (RGB, motion vectors, residuals) of a frame encoding, for further processing to perform the inference task. Pre-existing motion vector and/or residual information in frame encodings of the compressed video are leveraged to adaptively and efficiently perform the inference task. In some embodiments, the inference task is an action recognition task, such as a human action recognition task.

Abstract: A hole filling method for providing a virtual three-dimensional (3D) model, the hole filling method being executable on a computing device and including: acquiring an original learning image and a hole generation learning image for the original learning image, wherein the hole generation learning image is an image in which at least one hole is generated based on the original learning image; generating a hole filling learning image by performing hole filling on the hole generation learning image by using a neural network; performing a spherical transformation on each of the hole filling learning image and the original learning image; and training the neural network based on a difference between the spherically-transformed hole filling learning image and the spherically-transformed original learning image.

Abstract: Techniques are described for optimizing deep learning model performance using image harmonization as a pre-processing step. According to an embodiment, a method comprises decomposing, by a system operatively coupled to a processor, an input image into sub-images. The method further comprises harmonizing the sub-images with corresponding reference sub-images of at least one reference image based on two or more different statistical values respectively calculated for the sub-images and the corresponding reference-sub images, resulting in transformation of the sub-images into modified sub-images images. In some implementations, the modified sub-images can be combined into a harmonized image having a more similar appearance to the at least one reference image relative to the input image.

Abstract: Systems and methods are disclosed for correcting for artificial deformations in anatomical modeling. One method includes obtaining an anatomic model; obtaining information indicating a presence of an artificial deformation of the anatomic model; identifying a portion of the anatomic model associated with the artificial deformation; estimating a non-deformed local area corresponding to the portion of the anatomic model; and modifying the portion of the anatomic model associated with the artificial deformation, based on the estimated non-deformed local area.

Abstract: Patterning device modulates a light beam intensity distribution according to two-gradation first image data having a first number of pixels. Processing device calculates a correlation between detection intensity b based on output of photodetector and m-gradation (m?2) random second image data having a second number of pixels smaller than the first number, to generate a reconstructed image G(x,y) of an object. When the first and second image data are scaled to the same size and overlapped, each pixel is associated with a pixel group including multiple pixels of the overlapping first image data. With the normalized gradation value of a given pixel as k, the number of pixels included in the pixel group as L, and the number of pixels having a value of 1 in the pixel group as l, l=L×k holds true.

Abstract: The device (1) for estimating the distance between an observer (2) and a target (4) using at least one image generated by a digital image generator (6) from the position (P1) of the observer (2) comprises a detection and identification unit configured to detect and identify a target (4) in the image and define an imaged representation of the target (4), and a distance estimation unit configured to perform, on the image, multiple different projections of a three-dimensional model of the target (4) to obtain projected representations of the target (4) and to select the projected representation most similar to the imaged representation, the distance associated with the selected projected representation representing the estimated distance (D) between the position of the observer (2) and the target (4).

Abstract: A multimodal biometric device is disclosed. An apparatus may include a non-contact imaging system. The non-contact imaging system may include imaging optics, optical illumination optically coupled to the imaging optics, and a configurable body part support to support different body parts at corresponding focal lengths to capture different portions of the different body parts. An apparatus may also include a housing coupled to the imaging optics, the optical illumination, and the configurable body part support.

Abstract: Techniques are disclosed for generating a two-dimensional (2D) map of signal-to-noise ratio (SNR) values for sensor-acquired images. The techniques leverage the use of lookup tables (LUTs) to generate a transformation LUT that functions to map pixel values to SNR values. The transformation LUT may be generated by first generating an intermediate LUT that uses the operating parameters identified with the sensor to map pixel values to light level values. The light level values are then used together with an SNR model that outputs a prediction of electrons identified with a signal portion and a noise portion of images acquired by the sensor to thus map the pixel values to SNR values. The 2D map may be used to improve upon the accuracy of the classification of objects and/or scene characteristics for various applications.

Abstract: A system for indexing animated content receives detections extracted from a media file, where each one of the detections includes an image extracted from a corresponding frame of the media file that corresponds to a detected instance of an animated character. The system determines, for each of the received detections, an embedding defining a set of characteristics for the detected instance. The embedding associated with each detection is provided to a grouping engine that is configured to dynamically configure at least one grouping parameter based on a total number of the detections received. The grouping engine is also configured to sort the detections into groups using the grouping parameter and the embedding for each detection. A character ID is assigned to each one of the groups of detections, and the system indexes the groups of detections in a database in association with the character ID assigned to each group.

Abstract: According to some embodiments of the present disclosure, the disclosure relates to an application system and server kit that create and serve digital twin-enabled applications. This disclosure also relates to a hub-and-spoke classification system. This disclosure also relates to a location-based services framework that leverages a generative content process to improve location prediction. This disclosure also relates to virtual reality and augmented reality applications, as well as digital agents that support various types of applications.

Abstract: Disclosed are an information processing method and a terminal device. The method comprises: acquiring first information, wherein the first information is information to be processed by a terminal device; calling an operation instruction in a calculation apparatus to calculate the first information so as to obtain second information; and outputting the second information. By means of the examples in the present disclosure, a calculation apparatus of a terminal device can be used to call an operation instruction to process first information, so as to output second information of a target desired by a user, thereby improving the information processing efficiency. The present technical solution has advantages of a fast computation speed and high efficiency.

Abstract: A medical image region screening method and apparatus and a storage medium are provided. The method includes: obtaining a medical image of biological tissue, segmenting tissue regions of a plurality of tissue types from the medical image, selecting, from the tissue regions of the plurality of tissue types based on types of capturing positions of the medical image, a reserved region, obtaining a positional relationship between the reserved region and a predicted lesion region in the medical image; and screening for the predicted lesion region in the medical image based on the positional relationship, to obtain a target lesion region.

Abstract: A method of determining a measure of gaping in a fish fillet item, involves the steps of obtaining three-dimensional profile data of a first area of the fish fillet item, obtaining optical imaging data of a second area of the fish fillet item, wherein the first area and the second area are overlapping at least within an overlap area; and determining the measure of gaping in the fish fillet item based on the three-dimensional profile data within the overlap area and the optical imaging data within the overlap area.

Abstract: A system and method for improving a video characteristic of a video stream is described. According to various implementations of the invention, a changed region between a later-in-time image frame and an earlier-in-time image frame and an unchanged region between such two image frames are determined. A new improvement to the video characteristic is determined and applied to the changed region of the later-in-time image frame. A prior improvement to the video characteristic that was determined for the earlier-in-time image frame is applied to the unchanged region of the later-in-time image frame.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving multiple images from a camera, each image of the multiple images representative of a detection of an object within the image. For each image of the multiple images the methods include: determining a set of detected objects within the image, each object defined by a respective bounding box, and determining, from the set of detected objects within the image and ground truth labels, a false detection of a first object. The methods further include determining that a target object threshold is met based on a number of false detections of the first object in the multiple images, generating, based on the number of false detections for the first object meeting the target object threshold, an adversarial mask for the first object, and providing, to the camera, the adversarial mask.

Abstract: According to one embodiment, an information processing device includes acquisition means, detection means, and specifying means. The acquisition means acquires image data according to a lost article to which a symbol of a user is attached and identification information according to a group to which the user belongs. The detection means performs analysis set for each item of identification information according to the group with respect to the image data according to the lost article and detects the identification information for identifying the user included in the symbol. The specifying means specifies the user from the identification information detected by the detection means.

Abstract: The present invention discloses system and method for enhancing an image based on non-local features. The invention includes an end-to-end trainable and guided method including feature extraction block, non-local feature generator and non-local feature enhancement block, to deal with low-level image problem by using the non-local feature concept. The invention also deploys a non-local feature merge block to rectify translated features and improve non-local feature further to finally reconstruct the rectified features to form an enhanced image.